Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E2F2C660B24911A313B3D7C1FC707E1A76A3F30FA40AA9063AACE1951FD7CB5B662474 |
|
CONTENT
ssdeep
|
384:i9LZAFFGFjFhF3FwFRFuFiFoF5MRX97QN:igS5T1wjKmY5MRNI |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
993366cccecccc32 |
|
VISUAL
aHash
|
1800181818181818 |
|
VISUAL
dHash
|
204a323232323230 |
|
VISUAL
wHash
|
3c08183c3c3c3c3c |
|
VISUAL
colorHash
|
07008000c00 |
|
VISUAL
cropResistant
|
204a323232323230 |
Victim enters username and password into fake login form. Credentials are captured via JavaScript and exfiltrated to attacker's server in real-time.
Malicious code is obfuscated using 23 techniques to evade detection by security scanners and make reverse engineering more difficult.
Drainer supports multiple blockchain networks and checks for high-value tokens on each chain before executing drain operations.
Pages with identical visual appearance (based on perceptual hash)